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A Mixture Model for Survival Data with Both Latent and Non-Latent Cure Fractions

Author

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  • Eduardo Yoshio Nakano

    (Department of Statistics, University of Brasilia, Campus Darcy Ribeiro, Asa Norte, Brasilia 70910-900, Brazil)

  • Frederico Machado Almeida

    (Department of Statistics, University of Brasilia, Campus Darcy Ribeiro, Asa Norte, Brasilia 70910-900, Brazil)

  • Marcílio Ramos Pereira Cardial

    (Institute of Mathematics and Statistics, Federal University of Goias, Goiania 74001-970, Brazil)

Abstract

One of the most popular cure rate models in the literature is the Berkson and Gage mixture model. A characteristic of this model is that it considers the cure to be a latent event. However, there are situations in which the cure is well known, and this information must be considered in the analysis. In this context, this paper proposes a mixture model that accommodates both latent and non-latent cure fractions. More specifically, the proposal is to extend the Berkson and Gage mixture model to include the knowledge of the cure. A simulation study was conducted to investigate the asymptotic properties of maximum likelihood estimators. Finally, the proposed model is illustrated through an application to credit risk modeling.

Suggested Citation

  • Eduardo Yoshio Nakano & Frederico Machado Almeida & Marcílio Ramos Pereira Cardial, 2025. "A Mixture Model for Survival Data with Both Latent and Non-Latent Cure Fractions," Stats, MDPI, vol. 8(3), pages 1-15, September.
    • Handle: RePEc:gam:jstats:v:8:y:2025:i:3:p:82-:d:1748916
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